Accelerated nonrigid intensity-based image registration using importance sampling

IEEE Transactions on Medical Imaging

Volumn 28, Issue 8, 2009, Pages 1208-1216

  Bhagalia, Roshni ^a   Fessler, Jeffrey A ^a   Kim, Boklye ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

Gradient optimization; Importance sampling; Intensity based registration; Stochastic approximation

Indexed keywords

ADAPTIVE SAMPLING; BRAIN DATA; COMPUTATION TIME; COMPUTED TOMOGRAPHY; EMPIRICAL RESULTS; GRADIENT APPROXIMATION; GRADIENT DESCENT; GRADIENT OPTIMIZATION; IMAGE VOXELS; IMPORTANCE SAMPLING; INTENSITY-BASED; INTENSITY-BASED REGISTRATION; LARGE DATASETS; NONRIGID IMAGE REGISTRATION; RANDOM SUBSETS; REGISTRATION PROCESS; SIMILARITY METRICS; STOCHASTIC APPROXIMATION; STOCHASTIC APPROXIMATION METHODS; STOCHASTIC APPROXIMATIONS; WORK FOCUS;

ALGORITHMS; APPROXIMATION THEORY; COMPUTERIZED TOMOGRAPHY; IMAGE REGISTRATION; MULTIMEDIA SERVICES; OPTIMIZATION; WEAVING;

EDGE DETECTION;

ALGORITHM; ARTICLE; BRAIN; BREATHING MECHANICS; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE PROCESSING; LUNG; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; REPRODUCIBILITY;

ALGORITHMS; BRAIN; COMPUTER SIMULATION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LUNG; MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY OF RESULTS; RESPIRATORY MECHANICS; TOMOGRAPHY, X-RAY COMPUTED;

EID: 68249087871     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2009.2013136     Document Type: Article

References (24)

1. C. R. Meyer, J. L. Boes, B. Kim, P. H. Bland, K. R. Zasadny, P. V. Kison, K. Koral, K. A. Frey, and R. L. Wahl, "Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin plate spline warped geometric deformations," Med. Imag. Anal., vol. 1, no. 3, pp. 195-206, Apr. 1997.
2. P. Thévenaz and M. Unser, "Optimization of mutual information for multiresolution image registration," IEEE Trans. Imag. Process., vol. 9, no. 12, pp. 2083-2099, Dec. 2000.
3. D. Mattes, D. R. Haynor, H. Vesselle, T. K. Lewellen, and W. Eubank, "PET-CT image registration in the chest using free-form deformations," IEEE Trans. Med. Imag., vol. 22, no. 1, pp. 120-128, Jan. 2003.
4. D. Rueckert, P. Aljabar, R. A. Heckemann, J. V. Hajnal, and A. Hammers, "Diffeomorphic registration using B-splines," in Medical Image Comput. Computer-Assisted Intervention, 2006, pp. 702-709.
5. G. Christensen, R. D. Rabbitt, and M. I. Miller, "Deformable templates using large deformation kinematics," IEEE Trans. Imag. Process., vol. 5, no. 10, pp. 1435-1447, Oct. 1996.
6. J.-P. Thirion, "Image matching as a diffusion process: An analogy with Maxwell's demons," Med. Imag. Anal., vol. 2, no. 3, pp. 243-260, Sept. 1998.
7. S. Klein, M. Staring, and J. P. W. Pluim, "Evaluation of optimization methods for nonrigid medical image registration using mutual information and B-splines," IEEE Trans. Image Process., vol. 16, no. 12, pp. 2879-2890, Dec. 2007.
8. J. Kiefer and J. Wolfowitz, "Stochastic estimation of the maximum of a regression function," Ann. Math. Stat., vol. 23, no. 3, pp. 462-466, Sep. 1952.
9. J. C. Spall, "Multivariate stochastic approximation using a simultaneous perturbation gradient approximation," IEEE Trans. Autom. Control, vol. 37, no. 3, pp. 332-341, Mar. 1992.
10. H. Kushner and T. Gavin, "Extensions of Kesten's adaptive stochastic approximation method," Ann. Stat., vol. 1, no. 5, pp. 851-861, Sep. 1973.
11. H. Robbins and S. Monro, "A stochastic approximation method," Ann. Math. Stat., vol. 22, no. 3, pp. 400-407, Sep. 1951.
12. P. Dupuis and R. Simha, "On sampling controlled stochastic approximation," IEEE Trans. Autom. Control, vol. 36, no. 8, pp. 915-924, Aug. 1991.
13. S. Koonin, Computational Physics. Reading, MA: Addison-Wesley, 1986.
14. M. Unser, A. Aldroubi, and M. Eden, "B-spline signal processing: Part II-Efficient design and applications," IEEE Trans. Signal Process., vol. 41, no. 2, pp. 834-848, Feb. 1993.
15. M. R. Sabuncu and P. J. Ramadge, "Gradient based nonuniform sampling for information theoretic alignment methods," in Proc. Int. Conf. IEEE Eng. Med. Biol. Soc, 2004, vol. 3, pp. 1683-1686.
16. R. Bhagalia, J. A. Fessler, and B. Kim, "Gradient based image registration using importance sampling," in Proc. IEEE Int. Symp. Biomed. Imag., 2006, pp. 446-449.
17. H. Kesten, "Accelerated stochastic approximation," Ann. Math. Stat., vol. 29, no. 1, pp. 41-59, Mar. 1958.
18. J. Spall, "Implementation of the simultaneous perturbation algorithm for stochastic optimization," IEEE Trans. Aerosp. Electron. Syst., vol. 34, no. 3, pp. 817-823, Jul. 1998.
19. D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, "Design and construction of a realistic digital brain phantom," IEEE Trans. Med. Imag., vol. 17, no. 3, pp. 463-468, Jun. 1998.
20. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification. New York: Wiley, 2001.
21. M. M. Coselmon, J. M. Baiter, D. L. McShan, and M. L. Kessler, "Mutual information based CT registration of the lung at exhale and inhale breathing states using thin-plate splines," Med. Phys., vol. 31, no. 11, pp. 2942-2948, Nov. 2004.
22. E. Haber and J. Modersitzki, "Intensity gradient based registration and fusion of multi-modal images," in Proc. MICCAI, 2006, pp. 726-733.
23. J. P. W. Pluim, J. B. A. Maintz, and M. A. Viergever, "Image registration by maximization of combined mutual information and gradient information," IEEE Trans. Med. Imag., vol. 19, no. 8, pp. 809-814, Aug. 2000.
24. P. Thévenaz, M. Bierlaire, and M. Unser, "Halton sampling for image registration based on mutual information," Sampling Theory Signal Image Process., vol. 7, no. 2, pp. 141-171, May 2008.